Field of the Invention
The present invention relates to computer-assisted diagnosis, and more specifically relates to an avatar-based charting system and method whereby users watch a perspective view with the aid of concept maps, which integrates the information of medical images, laboratory examination, patient self-reporting, and expert consultation.
Description of Related Art
Tremendous amounts of data are generated in daily medical practice. Based on this data, doctors make decisions about how to treat and care for a patient. Therefore, it would be better if the data could be integrated and more effectively presented to the doctors and other medical staff.
The original thrust to computerize the medical record came from Larry Weed's seminal work in 1969. The P.O.M.R. elevated each of the patient's problems to the highest level in the chart and then organized the S.O.A.P. format as the means of reporting how the problem was doing in the follow-up visits. He also championed the use of flow sheets to follow the data that accumulated around the problems for simpler analysis.
In medical practice, there are various kinds of data coming from different sources. Some of them, for example, blood pressure, pulse rate, body temperature and urine volume, are observed by nurses several times every day. Others like biochemical or serological tests are measured by a laboratory once a week, month, or even year. The ability to do in depth epidemiological studies requires the option to access a large number of records to withdraw and collate disease data. However, it is difficult to access large numbers of paper medical records that may be required to carry out epidemiological studies. The fact that the records are largely hand written or typed makes this type of data access a laborious non-automatable task.
Human factors exacerbate this irregularity. Sometimes a patient may be asked the same questions many times by doctors, nurses, medical students and nursing interns. There are considerable differences among doctors in the style of clinical testing and treatment of patients' problems. Clinical data may be easily missed by human error or a complicated hospital system.
Traditional medical education in the transfer of knowledge and skills uses static text and pictures in the document, or literature. Recently, the medical information network has gradually developed so that it brings the convenience of applications. Schmeling et al. (2011) uses a network Learning System to design an autopsy tests digital platform, simulating an autopsy situation to enhance the ability of post-mortem examination. Colsman et al. (2006) develops an immunological digital learning platform as a teaching utility. O'Neill et al. (2011) utilizes a digital learning platform to strengthen the knowledge and control of infection prevention in health care for medical students, so that these medical students have better learning results then other students. Marshall et al. (2011) assesses medical students with a digital learning platform for radiology workflow testing. As a result, these medical students achieve better results. McKenna et al. (2010) teaches medical students to identify patients with chronic facial features in a digital learning method; the results show that the diagnostic capabilities of medical students are enhanced.
Taiwan patent TW-201301075 discloses a knowledge management system for medical images and a method for generating the related knowledge. The knowledge management system establishes a knowledge database with integration of medical images and the related texts. However, it does not provide a logical relation between the content of the data.
In the knowledge management and digital content field, Taiwan patent TW-I257592 discloses an interactive digital learning system without description of logical interpretation. Even the application TW-201218066 discloses an interface configuration system for multiple display areas, which uses a processing apparatus to command an adjustment module to provide an adjustment scheme through optimization analysis, and the adjustment scheme includes a reconfiguration of the sizes or shapes of the display areas, resealing of the display contents, and displaying the display contents by scrolling or paging.
The conventional system described above provides, for example, an integrated information and communication platform for outcome and evidence-based medical research. Using the system, clinicians have difficulting in developing a logical interpretation of the medical education in physiology, pathology and systemic areas. Nowadays, medical education is in the infancy in utilizing digital textbooks, digital learning, electronic medical records and records of care delivery model to assist the diagnosis and clinical experience. Through the system, researchers may also collaborate with colleagues to validate and to refine the study and invite patients to participate in the study. Patients may further access the study through the system.
There are other occasions when medical personnel have more time to obtain detailed information from and about the patient, and/or the patient can provide additional information by themselves. In these circumstances, a detailed fully automated approach to developing a diagnosis is desired. There are yet other occasions when various combinations of the above are desired depending on the time and information available.
In view of the foregoing, a need exists in the art for a computer-assisted diagnosis with logical interpretation. In addition, a need exists for such an avatar-based charting system installed in a mobile device.